Prediction

yuping322/test:97f149bb8b8850bdab77c52ca70df6501aace7a64222591371df216772d0b93a

Model

yuping322/test:97f149bb

hro553jbdr3zj2x36ota2y7zjq

Status

Succeeded

Source

Web

Hardware

Total duration

0.3s

Created

over 1 year ago

Input

image

{
  "image": "https://replicate.delivery/pbxt/K0nLUBXlUtduIl3p7kvxs5wsVckUh46nXm9iSuKfgxRS5rLh/1ba2826f41b62b203b98aed1ad86f31b.jpg"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yuping322/test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yuping322/test:97f149bb8b8850bdab77c52ca70df6501aace7a64222591371df216772d0b93a",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K0nLUBXlUtduIl3p7kvxs5wsVckUh46nXm9iSuKfgxRS5rLh/1ba2826f41b62b203b98aed1ad86f31b.jpg"
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run yuping322/test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yuping322/test:97f149bb8b8850bdab77c52ca70df6501aace7a64222591371df216772d0b93a",
    input={
        "image": "https://replicate.delivery/pbxt/K0nLUBXlUtduIl3p7kvxs5wsVckUh46nXm9iSuKfgxRS5rLh/1ba2826f41b62b203b98aed1ad86f31b.jpg"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run yuping322/test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "yuping322/test:97f149bb8b8850bdab77c52ca70df6501aace7a64222591371df216772d0b93a",
    "input": {
      "image": "https://replicate.delivery/pbxt/K0nLUBXlUtduIl3p7kvxs5wsVckUh46nXm9iSuKfgxRS5rLh/1ba2826f41b62b203b98aed1ad86f31b.jpg"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/yuping322/test@sha256:97f149bb8b8850bdab77c52ca70df6501aace7a64222591371df216772d0b93a \
  -i 'image="https://replicate.delivery/pbxt/K0nLUBXlUtduIl3p7kvxs5wsVckUh46nXm9iSuKfgxRS5rLh/1ba2826f41b62b203b98aed1ad86f31b.jpg"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 r8.im/yuping322/test@sha256:97f149bb8b8850bdab77c52ca70df6501aace7a64222591371df216772d0b93a
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image": "https://replicate.delivery/pbxt/K0nLUBXlUtduIl3p7kvxs5wsVckUh46nXm9iSuKfgxRS5rLh/1ba2826f41b62b203b98aed1ad86f31b.jpg"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

[ [ "n04584207", "wig", 0.5712125301361084 ], [ "n03404251", "fur_coat", 0.22934788465499878 ], [ "n03325584", "feather_boa", 0.023245569318532944 ] ]

Generated in

0.3 seconds

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